Future publics : long-term thinking and farsighted action in democratic systems
Bibliographic record
Abstract
Many scholars have argued that democracies cannot effectively address long-term problems because of the political dynamics of short electoral cycles, the immediate concerns of voters, the influence of powerful actors with dominant short-term interests, or the political impotence of future persons who do not yet exist. This dissertation explores and challenges these claims. I argue that democracy — in both theory and practice — can help encourage longer-term thinking and make collectively intentional farsighted actions possible. Much of what we know about the nature of intertemporal relations comes from theories of intergenerational justice. A justice-based approach is intuitively appealing because claims of justice are typically granted priority over claims of other types. Unlike political agreements, principles of justice cannot be legitimately ignored or abandoned in response to changing preferences or partisan motives. Nevertheless, I argue that we need to think not only about our justice-based obligations to the future but also about how the actions of individuals and groups can be coordinated such that collectively-desirable long-term objectives can be identified, specified, and achieved. Democracy is not just a system for registering existing views and preferences; it is also a means of shaping preferences and changing the expectations of individuals and groups. I argue that multilayered democratic systems that are comprised of both electoral and extra-electoral institutions, can help mitigate many of the problems identified by those who have argued that democracies are, by nature, short-sighted. At the large scale, democratic practices such as public deliberation make it possible for a society to talk to itself about what it is doing and where it wants to go. At the small scale, deliberation can help encourage longer-term thinking by creating conditions that favour other-regarding positions, including those that take into consideration the potential interests of future-others. Under certain conditions, democracies can create political imperatives that reward long-term thinking and turn short-term positions into political liabilities. While there are features of democratic systems that create and nurture short-term imperatives, democracies are not without resources for overcoming these challenges.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.067 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".